A Novel Transform Demodulation Algorithm for Motor Incipient Fault Detection

Niao Qing Hu, Lu Rui Xia, Feng Shou Gu, Guo Jun Qin

Research output: Contribution to journalArticle

32 Citations (Scopus)

Abstract

Faults, such as broken rotor bars, in induction motors may be detected by estimating the spectral signature of the stator currents, particularly the sidebands around the supply line frequency. However, the amplitude of the fundamental frequency (50 Hz) is considerably greater than the sideband amplitude. How to demodulate the signature frequency components under the heavy background of fundamental frequency, or how to remove the fundamental frequency, is becoming a key problem in motor current signature analysis. This paper puts forward a novel transform demodulation algorithm to solve the problem. The three-phase currents are transformed to a magnetic-torque (M-T) coordinate using this algorithm. It is found that the signature frequency components are demodulated in the magnetizing and torque-producing currents obtained by the transformation. Thus, the two demodulated M-T currents can be used to extract the enhanced signature frequency components of faults, and the incipient fault detection of induction motors is easy to realize. With both simulated and experimental data of broken rotor bars, it shows that the proposed algorithm can extract more detailed fault signature frequency components and realize the incipient fault detection of induction motors.

Original languageEnglish
Article number5570997
Pages (from-to)480-487
Number of pages8
JournalIEEE Transactions on Instrumentation and Measurement
Volume60
Issue number2
DOIs
Publication statusPublished - 1 Feb 2011

Fingerprint Dive into the research topics of 'A Novel Transform Demodulation Algorithm for Motor Incipient Fault Detection'. Together they form a unique fingerprint.

  • Cite this